Long intergenic non-protein coding RNA 02570 promotes nasopharyngeal carcinoma progression by adsorbing microRNA miR-4649-3p thereby upregulating both sterol regulatory element binding protein 1, and fatty acid synthase
Bibliographic record
Abstract
Our previous studies have elucidated a possible connection between long intergenic non-protein coding RNA 2570 (LINC02570) and nasopharyngeal carcinoma (NPC). However, the precise mechanism by which LINC02570 promotes NPC remains unknown. We used quantitative polymerase chain reaction (qPCR) to detect LINC02570 expression in nasopharyngeal cell lines, NPC tissues, and chronic rhinitis tissues. Subcellular LINC02570 localization was confirmed by fluorescence in situ hybridization (FISH). The effects of LINC02570 stable knockdown and overexpression on viabillity, proliferation, migration, and invasion were analyzed using 3-(4,5-Dimethyl-2-Thiazolyl)-2,5-Diphenyl-2-H-Tetrazolium bromide (MTT), a colorimetric focus-formation assay, a wound healing assay, and transwell assays. RNA crosstalk analysis in silico predicted microRNA-4649-3p (miR-4649-3p) binding to LINC02570 or sterol regulatory element binding transcription factor 1 (SREBF1). A dual luciferase reporter assay was used to confirm potential interactions. Sterol regulatory element binding protein 1 (SREBP1) and fatty acid synthase (FASN) expression were detected by western blotting. The results suggest that LINC02570 is upregulated in late clinical stage NPC patients, and promotes NPC progression by adsorbing miR-4649-3p to up-regulate SREBP1 and FASN. This study elucidates a potential chemotherapeutic target involved in lipid metabolism in NPC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".